Portfolio Optimization in a Downside Risk Framework (Optimisation De Portefeuille Dans Le Cadre Du Downside Risk)

Abstract

We showed in this article that the new mean-semivariance model for portfolio optimization makes it possible to overcome the drawbacks of the mean-variance model concerning the asymmetry of returns and the risk perception of investors. We also showed that this new mean-semivariance model permits to surmount the problem of inequality of the cosemivariances measures which occurs in the mean-semivariance model of Harlow (1991). The empirical investigation based on Morgan Stanley Capital Indices MSCI database of emerging markets demonstrates that the mean-variance model overestimates the risk because of the use of the variance as a risk measure, but the mean-semivariance model of Harlow (1991) underestimates the risk due to the cosemivariances measures used by this model. The results obtained also prove that the new mean-semivariance model provides a more correct portfolio optimization because it makes it possible to overcome all these problems.